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HABIT: Handwritten Analysis based Individualistic Traits Prediction
Abdul Rahiman, Diana Varghese, Manoj Kumar G
Pages - 209 - 218     |    Revised - 05-04-2013     |    Published - 30-04-2013
Published in International Journal of Image Processing (IJIP)
Volume - 7   Issue - 2    |    Publication Date - April 2013  Table of Contents
MORE INFORMATION
References   |   Cited By (3)   |   Abstracting & Indexing
KEYWORDS
Handwriting Analysis, Feature Extraction, Patterns.
ABSTRACT
Handwriting Analysis is a scientific method of identifying, evaluating and understanding an individual’s personality based on handwriting. Each personality trait of a person is represented by a neurological brain pattern. Each of these neurological brain patterns produces a unique neuromuscular movement that is the same for every person who has that particular personality trait. When writing, these tiny movements occur unconsciously. Strokes, patterns and pressure applied while writing can reveal specific personality traits. The true personality including emotional outlay, fears, honesty and defenses are revealed. Professional handwriting examiners called graphologists analyze handwriting samples for this purpose. However, accuracy of the analysis depends on how skilled the analyst is. The analyst is also prone to fatigue. High cost incurred is yet another deterrent. This paper aims at implementing an off-line, writer-independent handwriting analysis system “HABIT” (Handwriting Analysis Based Individualistic Traits Prediction) which acts as a tool to predict the personality traits of a writer automatically from features extracted from a scanned image of the writer’s handwriting sample given as input. The features include slant of baseline, pen pressure, slant of letters and size of writing. The implementation uses Java and Eclipse-Indigo as tools.
CITED BY (3)  
1 Kedar, S., Bormane, D. S., & Nair, V. (2016). Heart Disease Prediction Using k-Nearest Neighbor Classifier Based on Handwritten Text. In Computational Intelligence in Data Mining—Volume 1 (pp. 49-56). Springer India.
2 Kedar, S. V., Bormane, D. S., Dhadwal, A., Alone, S., & Agarwal, R. (2015, February). Automatic Emotion Recognition through Handwriting Analysis: A Review. In Computing Communication Control and Automation (ICCUBEA), 2015 International Conference on (pp. 811-816). IEEE.
3 Dias, C. (2014). Avaliação do património genético nos padrões fenotípicos da escrita.
ABSTRACTING & INDEXING
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
REFERENCES
AmeurBensefia , Ali Nosary, Thierry Paquet, Laurent Heutte,”WriterIdentification by Writer’s Invariants”,Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition”, pp 274-279, 2002.
Champa H N, K R AnandaKumar, “Automated Human Behavior Prediction through Handwriting Analysis”, IEEE First International Conference on Integrated Intelligent Computing, 2010.
N Mogharreban, S Rahimi, M Sabharwal, “A Combined Crisp and Fuzzy Approach for Handwriting Analysis”, IEEE Annual Meeting of the Fuzzy Information, vol 1,pp 351-356,2004.
OndrejRohlik, “Handwritten Text Analysis”, Department of Computer Science and Engineering Laboratory of Intelligent Communication Systems, University of West Bohemia In Pilsen, 2001.
Shitala Prasad, Vivek Kumar Singh, Akshay Sapre “Handwriting Analysis based on Segmentation Method for Prediction of Human Personality using Support Vector Machine”,International Journal of Computer Applications, Volume 8– No.12, October 2010.
Srihari S.N., Sung-Hyuk Cha and Sangjik Lee, “Establishing handwriting Individuality using pattern recognition techniques”, Proceedings of the Sixth International Conference on Document Analysis and Recognition, 2001.
Srihari S.N., Sung-Hyuk Cha and SangjikLee,“Establishing handwriting Individuality using pattern recognition techniques”,Proceedings of the Sixth International Conference on Document Analysis and Recognition, 2001.
Sunday Olatunbosun, Aaron Dancygier, Jayson Diaz, Stacy Bryan, and Sung-Hyuk Cha,”Automating the Lewinson-Zubin Handwriting Personality Assessment Scales”,Proceedings of Student-Faculty Research Day, CSIS, Pace University,2009.
MANUSCRIPT AUTHORS
Dr. Abdul Rahiman
Director, AICTE Ministry of HRD, Govt of India New Delhi - India
rehman_paika@yahoo.com
Miss Diana Varghese
Business Analyst, Mu Sigma Business Soln Pvt Ltd Bangalore - India
Dr. Manoj Kumar G
Associate Professor, Dept of Computer Science LBSITW,Trivandrum, Kerala - India


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